Initiated in automatic or controlled ways, selective attention refers to the cognitive processes that serve to filter relevant external and internal information for further processing (Stevens and Bavelier, 2012). In the context of emotional processing, selective attention is a crucial mechanism that influences our emotional experience and functioning by determining how the organism perceives and interprets emotional information in the environment (Gross et al., 2011; Sanchez et al., 2015). Attention bias is a sort of selective attention that occurs when individuals have high sensitivity to certain specific information (Bar-Haim et al., 2007). Studies have suggested that individual differences in attention bias underlie difficulties in emotion regulation processes, especially for depressed people (Joormann and D’Avanzato, 2010). Healthy individuals under negative emotion states transfer their attention more frequently to positive stimuli (Sanchez et al., 2014) and take attention away more rapidly from negative stimuli (Ellenbogen et al., 2002). However, individuals suffering from anxiety and depression show negative biases in selective attention (Armstrong and Olatunji, 2012). For instance, signal detection studies (Wiens et al., 2008) have found that individuals with anxiety disorders have lower detection thresholds for threatening stimuli, and research on spatial attention suggests that these decreased thresholds lead to increased orienting toward threats Mogg et al., 2002), which indicates that patients with anxiety disorders show attentional bias toward threats. This negative bias may increase state anxiety by causing increased awareness of threats (Armstrong and Olatunji, 2012). Besides, a small number of studies have observed reduced attention toward positive stimuli in depressed individuals relative to controls (Peckham et al., 2013). More seriously, people susceptible to depression have been characterized as attending to and remembering negative information (Siegle et al., 2002). This attentional style could lead to distorted beliefs and assumptions about the world (Armstrong and Olatunji, 2012).

The negative bias could be seen as reduced responsiveness or drive to engage with positive stimuli from surroundings, namely a positive attenuation effect. Alternatively, negative bias has been interpretable in terms of overwhelming attention to negative information, which can be thought of as a negative potentiation effect (Rottenberg et al., 2005). The attention bias toward negative stimuli would be related to a lack of inhibition of negative material, resulting from faulty inhibitory processes of interference control (Waters et al., 2006). Attentional bias mechanisms may be particularly active and impactful when processing socioemotional information, such as others’ emotional facial expressions (Gotlib et al., 2004a). Facial expressions are among the most commonly perceived visual stimuli and transmit and evoke emotion simultaneously. For instance, an attention bias toward sad or threatening faces more or less increases one’s negative emotions and leads to terrible representations in social communication (Frewen and Dozois, 2005). One of the hallmarks of depression is impaired social function, and previous research has documented that this manifestation stems from different attentional biases toward different facial expressions (Persad and Polivy, 1993).

Many behavioral studies have shown that there are some differences in the attention to different emotional faces between depressed and healthy groups. These findings can correspond to and verify the above hypotheses. Depressed groups gazed and engaged attention into negative faces for a longer time (Fritzsche et al., 2010), and were more likely to attend to negative facial expressions in a series of facial stimuli with different valence (Karparova et al., 2010). Even more, healthy subjects were more inclined to pay attention to negative faces after negative emotions’ induction (Kujawa et al., 2011). Some articles also reported that depressed groups attended to positive information insufficiently, manifesting that they pay less attention to happy faces than sad faces in the same conditions (Suslow et al., 2004). In general, depressed groups showed abnormally larger attention bias toward negative facial expressions compared with healthy controls.

Cognitive neuroscience has provided a new perspective on revealing brain mechanisms behind psychological phenomena theoretically and technically. There is an increase in the research on underlying neural correlates of attention biases toward facial expressions via neuroscience methods such as the event-related potentials (ERP) technique, which can uniquely complement traditional behavioral measures. Emotional facial expressions can evoke different ERP components well, some of that are related to attention processing (Schindler and Bublatzky, 2020). The P1, N1, and P2 belong to exogenous ERP components, which are easily affected by stimulus characteristics due to the early automatic attention mechanism, reflecting the bottom-up processing of attention. N2 and P3 are endogenous ERP components, occurring in later stages of processing and are closely related to cognition, reflecting the top-down processing of attention (Hopfinger and West, 2006; Brosch et al., 2011). Previous studies have reported that the abnormality of attention may be caused by the inefficient engagement of top-down control (Friedman-Hill et al., 2010; Delchau et al., 2019). Therefore, examining P3 and N2 could help discover the underlying neural processes behind attention biases to understand attention and inhibition behaviors better.

A new viewpoint noted that affect-biased attention is considered to be a form of emotion regulation (Bram et al., 2018). Growing evidence indicates that depression is always accompanied by dysregulation of emotion (Berking et al., 2014; Vanderlind et al., 2020). With the development of measuring methods in brain activities, frontal alpha asymmetry (FAA) has been increasingly seen as a reliable index of the capability of emotion regulation. FAA examines the activity of the left and right frontal alpha waves (typically at F3 and F4 electrodes). The intensity of alpha wave activity is inversely proportional to the intensity of activity in the corresponding cortical region. A strong alpha wave represents a weak activity in the brain and vice versa (Kline et al., 2007; Zhong et al., 2011). The left and right prefrontal cortex hemispheres show different attention biases to different emotional stimuli. The left frontal cortical activity is associated with positive effects, while the right frontal area might be susceptible to negative emotions (Davidson, 1998; Harmon-Jones et al., 2010). It is believed that individuals with high emotional regulation ability generally have greater left frontal activity (Dagmar Kr et al., 2010). The increase in left frontal activity tends to enhance the positive emotional experience (Tomarken et al., 1992). Anxiety and depressive symptoms caused by mood regulation disorders are associated with decreased left frontal lobe activity (Smit et al., 2007).

Neuroimaging studies demonstrate an interactive network of corticolimbic pathways playing a central role in the top-down regulation of emotions (Johnstone et al., 2007; Wager et al., 2008). Specifically, a functional balance between ventral [ventral anterior cingulate cortex (ACC), limbic structures] with dorsal compartments in the brain [dorsal ACC, dorsolateral prefrontal cortex (DLPFC)] is necessary for maintaining homeostatic emotional control (Ochsner and Gross, 2005). These brain structures are also involved in the attentional processing of emotional information (Fragopanagos et al., 2005), with the DLPFC as an important region for the implementation of top-down attentional control (MacDonald Angus et al., 2000). Therefore, emotional attentional biases associated with the dysregulation of emotional states can be understood as the result of failures in top-down attentional control implemented by the DLPFC (De Raedt et al., 2015). Therefore, the variation of activities in DLPFC might be associated with the formation of depression. Clinical studies have suggested that lesions of the left DLPFC are often associated with depression, while damages in the right DLPFC lead to elevated mood (Schmitz et al., 2006). Hypoactivity of the left DLPFC is thought to play a key role in the pathophysiology of depression, sometimes accompanied by increased right DLPFC functioning (Schutter and Honk, 2005; Hecht, 2010).

In recent years, transcranial direct current stimulation (tDCS) has shown promise as a neuromodulatory tool to study neuropsychological functioning (Shin et al., 2015). Constant low-intensity direct current (typically 0.5–2 mA) is applied to modulate spontaneous cortical activity. The application of current produces polarity-specific subthreshold changes in the excitability of underlying targeted cortical areas. Research has demonstrated that anodal stimulation increases cortical excitability, whereas cathodal stimulation decreases cortical activity (Nitsche and Paulus, 2001; Nitsche et al., 2003). To date, tDCS has been reported to significantly modulate a range of cognitive and affective abilities in healthy participants and patients with depression (Boggio et al., 2009; Wolkenstein and Plewnia, 2013; Salehinejad et al., 2016; Yadollahpour et al., 2017). However, few results have yielded the mechanism of tDCS. Combined with the importance of emotional attentional bias on patients, we hypothesized that tDCS could modulate the affective abilities of subjects by improving the negative cognitive bias.

In this study, we aimed to disentangle the effect of prefrontal tDCS on attention bias toward emotional information and emotion regulation abilities in healthy subjects. Considering the advantages of high temporal resolution and low cost, we used EEG to record the changes of cortical activity after tDCS to explore the neural correlation of attention towards emotional information. This study contained a rest task and a modified emotional oddball task consisting of six blocks, which could response attention bias. EEGs were recorded during rest and oddball task phases, respectively. Hereby, we selected healthy subjects rather than depressed patients to exclude the influence of clinical treatments such as antidepressant medications. Therefore, this study could be regarded as a preliminary attempt to investigate how appropriate tDCS protocol works in the treatment of depression. Since the main purpose is to explore the effects of tDCS in the treatment of depression, given the above-mentioned importance of the left DLPFC in depression, we performed only left DLPFC anodal stimulation in this study.

Recently, many researchers generally agreed that affect-biased attention is a form of emotion regulation. Also, affect-biased attention is tuned through experience over development (Todd et al., 2012), and individuals with different personality traits tend to show different attention biases (Paelecke et al., 2012). Several studies have suggested that depressive patients show a stronger attention bias for negative information, which may be related to the severity of depressive symptoms (Gotlib et al., 2004b; Sanchez et al., 2013). TDCS could improve depression and anxiety behaviors shown in clinical studies using enhancing cognitive control (Regni et al., 2010; Peña-Gómez et al., 2011). Few studies have explored the influence of tDCS on attentional bias. Thus, this study investigated attentional processing before and after tDCS within a healthy sample. TDCS reduced the commission error of taking neutral as negative, but there were no significant differences in the reaction time and accuracy. We found enhanced frontal alpha asymmetry coefficients after active tDCS treatment. The ERP results showed greater P3 amplitudes following positive targets and greater N2 amplitudes following negative distracters in the active tDCS group.

For behavioral data, only commission error of taking neutral as negative was significantly decreased after tDCS treatment and results including reaction time as well as accuracy showed no significant differences. It must be mentioned that all of the participants were healthy college students. It was not difficult for them to complete the simple oddball task. Therefore, we speculated there might exist the ceiling effect, resulting in the barely noticeable difference before and after tDCS treatment. And that is why we designed this study and analyzed the electrophysiological signals of the subjects. With high-time resolution, ERP could react to the real variations of subjects during the oddball task.

The P3 is thought to indicate processes involved in salient stimulus and is known to be modulated by attention (Becker and Shapiro, 1980; Heinze et al., 1990). The P3 amplitude has further been used to measure attentional allocation of cognitive processing resources in multiple tasks (Polich and Kok, 1995; Sawaki and Katayama, 2008). Affective stimuli can induce P3 signals well, and negative stimuli evokes greater P3 amplitudes than positive stimuli in healthy subjects (Morita et al., 2001). Compared to healthy groups, depressed individuals showed an enhanced P3 response to negative stimuli and a smaller P3 for positive stimuli (Ilardi et al., 2007). This can be seen as increased attention to the negative and a failure to attend sufficiently to the positive. However, many behavioral and psychophysiological findings showed that attention deficiency is widespread in anxiety, depression, and even attention deficit hyperactivity disorder (ADHD). Reduced P3 amplitude for task-relevant stimuli were observed in depressed groups as compared to the controls (Singh et al., 2000). In this study, we found increased P3 amplitudes following positive targets in the active group after receiving tDCS. This result suggests that tDCS may improve the allocation of attention to task-relevant positive stimuli in a healthy sample. P3 signals evoked by positive targets decreased significantly in the sham group. It is probably because the subjects’ attention to positive stimuli declined after being familiar with the paradigm.

Our results also provide somewhat evidence to suggest that tDCS may affect response inhibition to negative emotional stimuli in a healthy sample. In previous electrophysiological studies, the fronto-central N2 component has traditionally been interpreted as an index of response inhibition (Falkenstein et al., 1999; Falkenstein, 2006). Response inhibition research commonly applied Go/Nogo paradigms, which require the execution of a motor response on a Go stimulus and its inhibition on a Nogo stimulus (Kaiser et al., 2006). Decreased N2 amplitude has been implicated in a failure of inhibiting or task-irrelevant disinhibition. Accumulating evidence demonstrated that depression is associated with difficulty in inhibiting negative information. Some studies found abnormally decreased N2 amplitude following task-irrelevant or distracting negative affective pictures or facial stimuli in the depressed group (Joormann and Gotlib, 2008; Krompinger and Simons, 2009). From a general cognitive functioning perspective, this might be negative bias in attentional processing resulting in inhibitory deficits in the depressed group (Botvinick et al., 2001). We observed increased N2 following negative distracters significantly in the active group after treatment. Nevertheless, no significant amplitude changes were observed following positive distracters as well as in the sham group. Such difference before and after treatment could be explained in that tDCS may improve response inhibition to negative information in healthy subjects.

Besides, previous research on frontal lobe EEG lateralization found that frontal lobe EEG lateralization is associated with depression, anxiety, schizophrenia, aggressiveness, and other emotional and behavioral disorders (Aftanas and Pavlov, 2005; Mathersul et al., 2008; Reznik and Allen, 2017). A recent research’s result showed that frontal EEG lateralization can be used as a neurological indicator of depression (Gollan et al., 2014). Individuals with anxiety and depression have weakened left frontal lobe activity, while individuals with high emotional regulation ability have stronger left frontal lobe activity (Goodman et al., 2013). Thus, the implementation of emotional regulation and the use of emotional regulation strategies have enhanced left frontal lobe activity (Choi et al., 2016). In this study, we found that the FAA values of F4-F3 and F6-F5 positions increased significantly after tDCS in the active group, indicating the elevated emotion regulation ability.

Additionally, the DLPFC is of great importance in the top-down regulation of affective processing and highly correlated to emotion regulation (Baeken et al., 2010). Some studies have shown that tDCS has regulatory effects on DLPFC activity (Boggio et al., 2009) maybe by mediating cerebral blood flow and metabolism (Shiozawa et al., 2015). Anodal tDCS targeting the left DLPFC has reported significant antidepressant effects and improvement in emotional cognitive control, while tDCS over the right DLPFC leads to the generation of attentional impairments (Sanchez et al., 2016, 2018). A recent tDCS study showed a lateralized role of left and right DLPFC activity in enhancing/worsening the top-down regulation of emotional attention processing (Allaert et al., 2019). Our findings from two tasks were consistent with the above conclusions, illustrating the probable link between affect-bias attention and emotion regulation. But through Pearson correlation analysis and the mediating effect analysis, we did not find out the explicit link between ERP waveforms and FAA values statistically.

Some limitations should be considered in this study. First, our results could only reflect the effects of tDCS on electrophysiological data, while the results of behavioral data could not support the electrophysiological results. That means that the conclusions of this study are still inconclusive. TDCS could affect the subjects’ ERP and FAA, but the relationship between these results and emotional attention bias is still uncertain. In the above discussion, we only provide a possible explanation direction that these electrophysiological results may reflect attentional bias. Second, this study employed three types of emotional facial stimuli, i.e., positive, negative, and neutral, to analyze the affect-biased attention in emotional processing. However, we have made a basic classification of emotional stimuli only in terms of valence roughly. The effect of tDCS is unknown when the emotional stimulus is classified as multiple categories and dimensions in more fine-grained details. Third, our results should be considered in the light of our sample. We recruited a restricted sample from a young college student population with an education level above average. Thus, it remains to be elucidated whether results from this study generalize to other groups. Additionally, the results of the correlation analysis between FAA and ERP did not show the exact link between emotional processing and the functional connection of the prefrontal areas. Nonetheless, considering the underlying mechanism, future studies should think about how to explain the regulation of emotional attention by the prefrontal cortex better physiologically.

In sum, our findings offered some electrophysiological insight into how tDCS works in the treatment of depression. TDCS treatment may raise the level of attention allocation to the positive target stimulus, reduce the negative cognitive bias, and enhance emotion regulation ability. To some extent, results of ERP in oddball task and FAA in rest task may reflect the improvement of affect-bias attention and emotional regulation ability after tDCS. The above conclusions were only evidenced by physiological data significantly, excluding the inaccuracy and deception of self-assessment. Despite the limitations, this study adds to our understanding of changes that occurred in the brain region and may support the rationale for new therapies based on neuromodulation techniques. Future research is needed to replicate, extend, and refine these findings in depressed or dysphoric individuals to explore the feasibility of tDCS application toward emotional disorders.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by the Ethics Committee of Tianjin Hospital, Tianjin University. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

SL and DM conceived of the presented idea. SL designed the experiment. SZ performed the experiments. YH performed the computations. DG and SC verified the analytical methods. YK and DM helped supervise the project. All authors discussed the results and contributed to the final manuscript.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.